Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32927
Title: A hybrid scheduling decision support model for minimizing job tardiness in a make-to-order based mould manufacturing environment
Authors: Choy, KL 
Leung, YK
Chow, HKH
Poon, TC
Kwong, CK 
Ho, GTS
Kwok, SK
Keywords: Genetic Algorithm
Make-to-order
Operation management
Production planning
Scheduling
Issue Date: 2011
Publisher: Pergamon Press
Source: Expert systems with applications, 2011, v. 38, no. 3, p. 1931-1941 How to cite?
Journal: Expert systems with applications 
Abstract: In the make-to-order (MTO) mode of manufacturing, the specification of each product is unique such that production processes vary from one product to another making the production schedule complex. In order to achieve high level productivity, the production flow is not arranged in sequence; instead, the job schedule of different production jobs is adjusted to fit in with the multiple-job shop environment. A poor scheduling of jobs leads to high production cost, long production time and tardiness in job performance. The existing of tardiness in the production schedule significantly affects the harmony among the multiple jobs on the shops floor. In order to provide a complete solution for solving MTO scheduling problems with job shifting and minimizing job tardiness, a hybrid scheduling decision support model (SDSM) is introduced. The model is combined by a Genetic Algorithm (GA) and an optimisation module. GA is adopted to solve the complex scheduling problem taking into consideration of the wide variety of processes while the optimisation module is suggested for tackling tardiness in doing the jobs in a cost effective way. The simulation results reveal that the model shortens the generation time of production schedules and reduces the production cost in MTO-based production projects.
URI: http://hdl.handle.net/10397/32927
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2010.07.125
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